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A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy

Although local advanced gastric cancer (AGC) could benefit from neoadjuvant radiotherapy (NRT), there are few studies evaluating patients survival after NRT. In current study, we aimed to investigate the value of prognostic factors in AGC patients after NRT and to evaluate whether post-therapy patho...

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Autores principales: Liu, Jianjun, Su, Mingxue, Wang, Jing, Zhang, Gan, Zhou, Jing, Zhang, Anqing, Ren, Zixue, Zheng, Xucai, Hong, Shikai, Wang, Shengying, Zhang, Rongxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355162/
https://www.ncbi.nlm.nih.gov/pubmed/27740935
http://dx.doi.org/10.18632/oncotarget.12573
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author Liu, Jianjun
Su, Mingxue
Wang, Jing
Zhang, Gan
Zhou, Jing
Zhang, Anqing
Ren, Zixue
Zheng, Xucai
Hong, Shikai
Wang, Shengying
Zhang, Rongxin
author_facet Liu, Jianjun
Su, Mingxue
Wang, Jing
Zhang, Gan
Zhou, Jing
Zhang, Anqing
Ren, Zixue
Zheng, Xucai
Hong, Shikai
Wang, Shengying
Zhang, Rongxin
author_sort Liu, Jianjun
collection PubMed
description Although local advanced gastric cancer (AGC) could benefit from neoadjuvant radiotherapy (NRT), there are few studies evaluating patients survival after NRT. In current study, we aimed to investigate the value of prognostic factors in AGC patients after NRT and to evaluate whether post-therapy pathological characteristics were predictive factors in these patients. We retrospectively analyzed AGC patients who underwent NRT from Surveillance, Epidemiology, and End Results (SEER) Database. The patients clinical and post-therapy pathological characteristics were analyzed. The best cutoff points for continuous variables were identified by X-tile. The discrimination of risk factors were compared by receiver operating characteristic (ROC) curve. As a result, 1,429 AGC patients were included into this study. In the multivariate analysis, the lymph nodes status and histology grade were significant risk factors for DSS (disease special survival). Then, we propose a novel Grade-lymph node Ratio (G-R) staging system for the AGC patients survival prognosis. Clearly, the new G-R staging system has a more-accurate 3-year and 5-year DSS prediction than the AJCC staging system (p = 0.001, 0.007, respectively). In conclusions, the current large, general population-based study demonstrated that the G-R staging system resulting in more-accurate DSS prediction. It could be regarded as a reliable classification for AGC patients after NRT in future.
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spelling pubmed-53551622017-04-15 A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy Liu, Jianjun Su, Mingxue Wang, Jing Zhang, Gan Zhou, Jing Zhang, Anqing Ren, Zixue Zheng, Xucai Hong, Shikai Wang, Shengying Zhang, Rongxin Oncotarget Clinical Research Paper Although local advanced gastric cancer (AGC) could benefit from neoadjuvant radiotherapy (NRT), there are few studies evaluating patients survival after NRT. In current study, we aimed to investigate the value of prognostic factors in AGC patients after NRT and to evaluate whether post-therapy pathological characteristics were predictive factors in these patients. We retrospectively analyzed AGC patients who underwent NRT from Surveillance, Epidemiology, and End Results (SEER) Database. The patients clinical and post-therapy pathological characteristics were analyzed. The best cutoff points for continuous variables were identified by X-tile. The discrimination of risk factors were compared by receiver operating characteristic (ROC) curve. As a result, 1,429 AGC patients were included into this study. In the multivariate analysis, the lymph nodes status and histology grade were significant risk factors for DSS (disease special survival). Then, we propose a novel Grade-lymph node Ratio (G-R) staging system for the AGC patients survival prognosis. Clearly, the new G-R staging system has a more-accurate 3-year and 5-year DSS prediction than the AJCC staging system (p = 0.001, 0.007, respectively). In conclusions, the current large, general population-based study demonstrated that the G-R staging system resulting in more-accurate DSS prediction. It could be regarded as a reliable classification for AGC patients after NRT in future. Impact Journals LLC 2016-10-11 /pmc/articles/PMC5355162/ /pubmed/27740935 http://dx.doi.org/10.18632/oncotarget.12573 Text en Copyright: © 2017 Liu et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Clinical Research Paper
Liu, Jianjun
Su, Mingxue
Wang, Jing
Zhang, Gan
Zhou, Jing
Zhang, Anqing
Ren, Zixue
Zheng, Xucai
Hong, Shikai
Wang, Shengying
Zhang, Rongxin
A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
title A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
title_full A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
title_fullStr A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
title_full_unstemmed A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
title_short A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
title_sort novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy
topic Clinical Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355162/
https://www.ncbi.nlm.nih.gov/pubmed/27740935
http://dx.doi.org/10.18632/oncotarget.12573
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